Overview

Dataset statistics

Number of variables10
Number of observations196
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.8 KiB
Average record size in memory82.7 B

Variable types

Categorical6
Text1
Boolean3

Dataset

Description한국철도공사와 서울교통공사에 서 운영하는 수도권 1호선의 승강장 정보에 대한 데이터로 철도운영기관명, 선명, 역명, 승강장번호, 상하행구분, 지상구분, 역층, 승강장연결 여부, 스크린도어 유무, 안전발판 유무의 데이터가 있습니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15041192/fileData.do

Alerts

선명 has constant value ""Constant
지상구분 is highly overall correlated with 철도운영기관명High correlation
승강장번호 is highly overall correlated with 상하행High correlation
철도운영기관명 is highly overall correlated with 지상구분High correlation
상하행 is highly overall correlated with 승강장번호High correlation
철도운영기관명 is highly imbalanced (52.5%)Imbalance
승강장연결 여부 is highly imbalanced (80.3%)Imbalance

Reproduction

Analysis started2023-12-12 14:21:44.300035
Analysis finished2023-12-12 14:21:45.079775
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
코레일
176 
서울교통공사
20 

Length

Max length6
Median length3
Mean length3.3061224
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row코레일
2nd row코레일
3rd row코레일
4th row코레일
5th row코레일

Common Values

ValueCountFrequency (%)
코레일 176
89.8%
서울교통공사 20
 
10.2%

Length

2023-12-12T23:21:45.143917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:21:45.240461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
코레일 176
89.8%
서울교통공사 20
 
10.2%

선명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
1호선
196 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1호선
2nd row1호선
3rd row1호선
4th row1호선
5th row1호선

Common Values

ValueCountFrequency (%)
1호선 196
100.0%

Length

2023-12-12T23:21:45.592917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:21:45.666302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1호선 196
100.0%

역명
Text

Distinct98
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T23:21:45.909188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length2
Mean length2.6530612
Min length2

Characters and Unicode

Total characters520
Distinct characters117
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가능
2nd row가능
3rd row가산디지털단지
4th row가산디지털단지
5th row간석
ValueCountFrequency (%)
가능 2
 
1.0%
의왕 2
 
1.0%
용산 2
 
1.0%
외대앞 2
 
1.0%
온양온천 2
 
1.0%
온수 2
 
1.0%
오산대 2
 
1.0%
오산 2
 
1.0%
오류동 2
 
1.0%
영등포 2
 
1.0%
Other values (88) 176
89.8%
2023-12-12T23:21:46.261262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 24
 
4.6%
천 20
 
3.8%
산 20
 
3.8%
대 18
 
3.5%
정 12
 
2.3%
도 10
 
1.9%
서 10
 
1.9%
신 10
 
1.9%
구 8
 
1.5%
양 8
 
1.5%
Other values (107) 380
73.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 504
96.9%
Close Punctuation 6
 
1.2%
Open Punctuation 6
 
1.2%
Decimal Number 4
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 24
 
4.8%
천 20
 
4.0%
산 20
 
4.0%
대 18
 
3.6%
정 12
 
2.4%
도 10
 
2.0%
서 10
 
2.0%
신 10
 
2.0%
구 8
 
1.6%
양 8
 
1.6%
Other values (103) 364
72.2%
Decimal Number
ValueCountFrequency (%)
3 2
50.0%
5 2
50.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 504
96.9%
Common 16
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 24
 
4.8%
천 20
 
4.0%
산 20
 
4.0%
대 18
 
3.6%
정 12
 
2.4%
도 10
 
2.0%
서 10
 
2.0%
신 10
 
2.0%
구 8
 
1.6%
양 8
 
1.6%
Other values (103) 364
72.2%
Common
ValueCountFrequency (%)
) 6
37.5%
( 6
37.5%
3 2
 
12.5%
5 2
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 504
96.9%
ASCII 16
 
3.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 24
 
4.8%
천 20
 
4.0%
산 20
 
4.0%
대 18
 
3.6%
정 12
 
2.4%
도 10
 
2.0%
서 10
 
2.0%
신 10
 
2.0%
구 8
 
1.6%
양 8
 
1.6%
Other values (103) 364
72.2%
ASCII
ValueCountFrequency (%)
) 6
37.5%
( 6
37.5%
3 2
 
12.5%
5 2
 
12.5%

승강장번호
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
1
98 
2
98 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 98
50.0%
2 98
50.0%

Length

2023-12-12T23:21:46.378185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:21:46.453161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 98
50.0%
2 98
50.0%

상하행
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
상행
98 
하행
98 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상행
2nd row하행
3rd row하행
4th row상행
5th row하행

Common Values

ValueCountFrequency (%)
상행 98
50.0%
하행 98
50.0%

Length

2023-12-12T23:21:46.531561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:21:46.610282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상행 98
50.0%
하행 98
50.0%

지상구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
지상
174 
지하
22 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지상
2nd row지상
3rd row지상
4th row지상
5th row지상

Common Values

ValueCountFrequency (%)
지상 174
88.8%
지하 22
 
11.2%

Length

2023-12-12T23:21:46.692384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:21:46.771501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지상 174
88.8%
지하 22
 
11.2%

역층
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2
96 
1
88 
3
12 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 96
49.0%
1 88
44.9%
3 12
 
6.1%

Length

2023-12-12T23:21:46.856563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:21:47.001909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 96
49.0%
1 88
44.9%
3 12
 
6.1%

승강장연결 여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
True
190 
False
 
6
ValueCountFrequency (%)
True 190
96.9%
False 6
 
3.1%
2023-12-12T23:21:47.081168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

스크린도어 유무
Boolean

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
False
100 
True
96 
ValueCountFrequency (%)
False 100
51.0%
True 96
49.0%
2023-12-12T23:21:47.166215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

안전발판 유무
Boolean

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
True
168 
False
28 
ValueCountFrequency (%)
True 168
85.7%
False 28
 
14.3%
2023-12-12T23:21:47.246567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:21:47.325342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
철도운영기관명역명승강장번호상하행지상구분역층승강장연결 여부스크린도어 유무안전발판 유무
철도운영기관명1.0001.0000.0000.0000.9920.2020.0780.4820.139
역명1.0001.0000.0000.0001.0001.0001.0001.0001.000
승강장번호0.0000.0001.0001.0000.0000.0000.0000.0000.000
상하행0.0000.0001.0001.0000.0000.0000.0000.0000.000
지상구분0.9921.0000.0000.0001.0000.2140.3910.4170.000
역층0.2021.0000.0000.0000.2141.0000.1280.0000.100
승강장연결 여부0.0781.0000.0000.0000.3910.1281.0000.0000.000
스크린도어 유무0.4821.0000.0000.0000.4170.0000.0001.0000.000
안전발판 유무0.1391.0000.0000.0000.0000.1000.0000.0001.000
2023-12-12T23:21:47.440426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지상구분역층승강장번호철도운영기관명안전발판 유무승강장연결 여부상하행스크린도어 유무
지상구분1.0000.3490.0000.9210.0000.2560.0000.274
역층0.3491.0000.0000.3300.1650.2110.0000.000
승강장번호0.0000.0001.0000.0000.0000.0000.9900.000
철도운영기관명0.9210.3300.0001.0000.0880.0490.0000.320
안전발판 유무0.0000.1650.0000.0881.0000.0000.0000.000
승강장연결 여부0.2560.2110.0000.0490.0001.0000.0000.000
상하행0.0000.0000.9900.0000.0000.0001.0000.000
스크린도어 유무0.2740.0000.0000.3200.0000.0000.0001.000
2023-12-12T23:21:47.553105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
철도운영기관명승강장번호상하행지상구분역층승강장연결 여부스크린도어 유무안전발판 유무
철도운영기관명1.0000.0000.0000.9210.3300.0490.3200.088
승강장번호0.0001.0000.9900.0000.0000.0000.0000.000
상하행0.0000.9901.0000.0000.0000.0000.0000.000
지상구분0.9210.0000.0001.0000.3490.2560.2740.000
역층0.3300.0000.0000.3491.0000.2110.0000.165
승강장연결 여부0.0490.0000.0000.2560.2111.0000.0000.000
스크린도어 유무0.3200.0000.0000.2740.0000.0001.0000.000
안전발판 유무0.0880.0000.0000.0000.1650.0000.0001.000

Missing values

2023-12-12T23:21:44.860370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:21:45.027395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

철도운영기관명선명역명승강장번호상하행지상구분역층승강장연결 여부스크린도어 유무안전발판 유무
0코레일1호선가능1상행지상2YNN
1코레일1호선가능2하행지상2YNN
2코레일1호선가산디지털단지2하행지상1YYN
3코레일1호선가산디지털단지1상행지상1YYN
4코레일1호선간석2하행지상1YYN
5코레일1호선간석1상행지상1YYN
6코레일1호선개봉1상행지상1YYY
7코레일1호선개봉2하행지상1YYY
8코레일1호선관악2하행지상1YYY
9코레일1호선관악1상행지상1YYY
철도운영기관명선명역명승강장번호상하행지상구분역층승강장연결 여부스크린도어 유무안전발판 유무
186서울교통공사1호선제기동2하행지하2YYY
187서울교통공사1호선제기동1상행지하2YYY
188서울교통공사1호선종각2하행지하2NYY
189서울교통공사1호선종각1상행지하2NYY
190서울교통공사1호선종로3가2하행지하2YYY
191서울교통공사1호선종로3가1상행지하2YYY
192서울교통공사1호선종로5가1상행지하2YYY
193서울교통공사1호선종로5가2하행지하2YYY
194서울교통공사1호선청량리(서울시립대입구)2하행지하2YYY
195서울교통공사1호선청량리(서울시립대입구)1상행지하2YYY